Cargando…

Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis

Medullary thyroid carcinoma (MTC) is an endocrine tumor and comprises 5–10% of all primary thyroid malignancies. However, the biomechanical contribution to the development and progression of MTC remains unclear. In this study, To discover the key microRNAs (miRNAs or miRs) and their potential roles...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Lijie, Lu, Donghui, Liu, Meiqin, Zhang, Mingjin, Peng, Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691269/
https://www.ncbi.nlm.nih.gov/pubmed/31322209
http://dx.doi.org/10.3892/mmr.2019.10463
_version_ 1783443333916393472
author Zhang, Lijie
Lu, Donghui
Liu, Meiqin
Zhang, Mingjin
Peng, Quan
author_facet Zhang, Lijie
Lu, Donghui
Liu, Meiqin
Zhang, Mingjin
Peng, Quan
author_sort Zhang, Lijie
collection PubMed
description Medullary thyroid carcinoma (MTC) is an endocrine tumor and comprises 5–10% of all primary thyroid malignancies. However, the biomechanical contribution to the development and progression of MTC remains unclear. In this study, To discover the key microRNAs (miRNAs or miRs) and their potential roles in the tumorigenesis of MTC, the microarray datasets GSE97070, GSE40807 and GSE27155 were analyzed. The datasets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed miRNAs (DEMs) and genes (DEGs) were accessed by R. Targets of DEMs and predicted using starBase, and functional and pathway enrichment analyses were performed using Metascape. A protein-protein interaction (PPI) network and an analysis of modules were constructed using NetworkAnalyst. Finally, a network was constructed to show the regulatory association between transcription factors (TFs), DEMs and downstream genes. A total of 5 DEMs were found both in GSE97070 and GSE40807, including 3 upregulated DEMs and 2 downregulated DEMs. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses from Metascape revealed that the target genes of upregulated DEMs were significantly enriched in adherens junction, kinase and protein binding, while the target genes of downregulated DEMs were mainly involved in non-canonical Wnt signaling pathway and RNA transport. From the PPI network, 13 nodes were screened as hub genes. Pathway enrichment analysis revealed that the top 5 modules were mostly enriched in the neurotrophin signaling pathway, mRNA surveillance pathway and MAPK signaling pathway. In addition, the TF-DEMs-target gene and DEGs regulatory network revealed that 17 TFs regulated 2 miRNAs, including upregulated or downregulated DEMs, CREB1 regulated all upregulated DEMs, and TGFB1 was an activator of hsa-miR-199a-3p and a repressor of hsa-miR-429. Taken together, the present study identified several miRNAs and potential biological mechanisms involved in the tumorigenesis of MTC. This study identified the key DEMs and potential mechanisms underlying the development of MTC, and provided a series of biomarkers and targets for the management of MTC.
format Online
Article
Text
id pubmed-6691269
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher D.A. Spandidos
record_format MEDLINE/PubMed
spelling pubmed-66912692019-08-19 Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis Zhang, Lijie Lu, Donghui Liu, Meiqin Zhang, Mingjin Peng, Quan Mol Med Rep Articles Medullary thyroid carcinoma (MTC) is an endocrine tumor and comprises 5–10% of all primary thyroid malignancies. However, the biomechanical contribution to the development and progression of MTC remains unclear. In this study, To discover the key microRNAs (miRNAs or miRs) and their potential roles in the tumorigenesis of MTC, the microarray datasets GSE97070, GSE40807 and GSE27155 were analyzed. The datasets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed miRNAs (DEMs) and genes (DEGs) were accessed by R. Targets of DEMs and predicted using starBase, and functional and pathway enrichment analyses were performed using Metascape. A protein-protein interaction (PPI) network and an analysis of modules were constructed using NetworkAnalyst. Finally, a network was constructed to show the regulatory association between transcription factors (TFs), DEMs and downstream genes. A total of 5 DEMs were found both in GSE97070 and GSE40807, including 3 upregulated DEMs and 2 downregulated DEMs. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses from Metascape revealed that the target genes of upregulated DEMs were significantly enriched in adherens junction, kinase and protein binding, while the target genes of downregulated DEMs were mainly involved in non-canonical Wnt signaling pathway and RNA transport. From the PPI network, 13 nodes were screened as hub genes. Pathway enrichment analysis revealed that the top 5 modules were mostly enriched in the neurotrophin signaling pathway, mRNA surveillance pathway and MAPK signaling pathway. In addition, the TF-DEMs-target gene and DEGs regulatory network revealed that 17 TFs regulated 2 miRNAs, including upregulated or downregulated DEMs, CREB1 regulated all upregulated DEMs, and TGFB1 was an activator of hsa-miR-199a-3p and a repressor of hsa-miR-429. Taken together, the present study identified several miRNAs and potential biological mechanisms involved in the tumorigenesis of MTC. This study identified the key DEMs and potential mechanisms underlying the development of MTC, and provided a series of biomarkers and targets for the management of MTC. D.A. Spandidos 2019-09 2019-07-03 /pmc/articles/PMC6691269/ /pubmed/31322209 http://dx.doi.org/10.3892/mmr.2019.10463 Text en Copyright: © Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Zhang, Lijie
Lu, Donghui
Liu, Meiqin
Zhang, Mingjin
Peng, Quan
Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis
title Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis
title_full Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis
title_fullStr Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis
title_full_unstemmed Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis
title_short Identification and interaction analysis of key miRNAs in medullary thyroid carcinoma by bioinformatics analysis
title_sort identification and interaction analysis of key mirnas in medullary thyroid carcinoma by bioinformatics analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691269/
https://www.ncbi.nlm.nih.gov/pubmed/31322209
http://dx.doi.org/10.3892/mmr.2019.10463
work_keys_str_mv AT zhanglijie identificationandinteractionanalysisofkeymirnasinmedullarythyroidcarcinomabybioinformaticsanalysis
AT ludonghui identificationandinteractionanalysisofkeymirnasinmedullarythyroidcarcinomabybioinformaticsanalysis
AT liumeiqin identificationandinteractionanalysisofkeymirnasinmedullarythyroidcarcinomabybioinformaticsanalysis
AT zhangmingjin identificationandinteractionanalysisofkeymirnasinmedullarythyroidcarcinomabybioinformaticsanalysis
AT pengquan identificationandinteractionanalysisofkeymirnasinmedullarythyroidcarcinomabybioinformaticsanalysis